E-nose UFGC Detects if Meat Traders Have Been Telling Porkies

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  • Published: Apr 17, 2017
  • Author: Ryan De Vooght-Johnson
  • Channels: Gas Chromatography
thumbnail image: E-nose UFGC Detects if Meat Traders Have Been Telling Porkies

Differentiation between thawed frozen and chilled meat a challenge

The meat industry is multi-billion pound international business involving a huge variety of producers, wholesalers and retailers. It is important for retailers and regulatory bodies to be able to differentiate between fresh chilled meat and frozen meat that has been thawed since the price differential leads to a temptation to pass the latter off as the former. It is also necessary to be able to determine the true age of chilled meat since it has a limited shelf life.

The smell of meat is often used by consumers as an indicator of freshness, although this may be more evident after cooking than in the chilled raw state. GC is often used to characterise meat, but there is no clear correlation between the chromatogram given by the conventional GC of meat products and the perception of their odour.

In order to overcome the limitations of conventional GC, electronic nose devices, or e-noses, have been developed. These mimic to some extent the human nose, giving an overall odour pattern, rather than focusing on the assay of a few compounds. The scientists from Warsaw and Dublin used an e-nose device to examine samples of frozen and chilled pork neck.

E-nose with dual UFGC columns used for pork volatiles

Six pork necks were used, with 12 slices being taken from each and then vacuum packed. For each group of twelve, three slices were stored chilled for one day, three for four days, three for seven days and the remaining three slices were frozen for five months, then thawed. It was found that neither pH nor colour changes could reliably be used to differentiate between the different storage regimes.

An e-nose device, an Alpha MOS Heracles II electronic nose, was used to examine volatiles from samples taken from the meat slices. The e-nose used headspace analysis combined with two ultra-fast gas chromatography columns (UFGC), DB-5 and DB-1701, run in parallel. The meat samples were sealed in vials and heated at 55 °C for 15 minutes in order to produce volatiles. An autosampler transferred volatiles from the headspace to a trap (Tenax); they were then run on the two columns in parallel, with a gradient from 40 to 270 °C and a run time of less than 2 minutes. Three repetitions were carried out per sample. Kovat’s retention indices (i.e. relative retention indices) were calculated and compared with figures from the AroChemBase library, a database of around 44,000 compounds.

There were some clear differences between the groups of samples. The one-day chilled samples exhibited relatively few volatiles, with more appearing in the four-day and seven-day samples. The frozen samples were distinctive, with more aldehydes than the chilled samples. Statistica software version 12 was employed for statistical analysis. Principal component analysis (PCA) was used to group the samples into three distinct groups: firstly, one-day chilled samples, secondly, four-day and seven-day chilled samples and, lastly, frozen samples.

Discriminant factor analysis (DFA) was used to categorise the samples. Half the samples analysed were used as ‘training’ samples for the DFA, while the remainder were treated as unknowns for model validation. The overall accuracy of the DFA model for assigning samples to the correct category was 78%, with the one-day chilled samples and the frozen samples being the most readily identified.

E-Nose and DFA method distinguishes between meat samples

The use of the e-nose and DFA is a fast and relatively inexpensive method of distinguishing between fresh chilled meat samples and those that have been previously frozen. Although the method is not yet 100% accurate, it is good enough to flag up cases that require further investigation. Doubtless further refinement, such as the use of larger training sets of data for the DFA, will improve the accuracy. It will be interesting to see how well the system performs with other types of meat.

Related Links

Journal of Food Process Engineering, 2017. Górska-Horczyczak et al. Differentiation of chill-stored and frozen pork necks using electronic nose with ultra-fast gas chromatography.

Wikipedia, Electronic Nose

Article by Ryan De Vooght-Johnson

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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